Open-source Claude Code skill diagnoses AI adoption roadblocks
An open-source Claude Code skill called the AI Adoption Playbook helps diagnose where companies are stuck with AI implementation and creates actionable plans. The tool is MIT licensed and available on GitHub.
What it does
The playbook runs inside Claude Code and performs three specific functions:
- Diagnoses where AI adoption is stuck—identifying issues with tooling, culture, measurement, or combinations of these factors
- Builds a 90-day plan with named owners and concrete milestones
- Pressure-tests board narratives before presentation
Development background
The creator spent months interviewing 100+ founders and board members about AI adoption, identifying common patterns: difficulty measuring ROI cleanly, board frustration with vague "we're exploring it" statements, and successful companies having one person who owns AI adoption.
The tool is designed to address these specific pain points by providing structured analysis and planning directly within the Claude Code environment.
Availability and feedback
The playbook is available at https://github.com/adimango/ai-adoption-playbook. The creator is specifically seeking feedback on the Claude Code integration to improve its usefulness for developers working with AI coding agents.
📖 Read the full source: r/ClaudeAI
👀 See Also
Arena AI Model ELO History Tracks LLM Performance Decay Over Time
A live dashboard visualizes ELO ratings of flagship models from major AI labs, revealing gradual performance degradation and sudden jumps at new releases. The tool dynamically plots one curve per lab, tracking the highest-rated model.
dead-letter: Local .eml to .md Converter with CLI, Web UI, and MCP Server
dead-letter normalizes email exports into Markdown with YAML front matter, customisable. It offers four access modes: CLI, Python library, Web UI, and an MCP server for direct integration with Claude Desktop, Claude Code, and Codex.
AI Token Monitor: macOS Tool Tracks Local Claude Usage and Cost
A developer built AI Token Monitor, a macOS menu bar app that reads local Claude session files to track token usage, model distribution, and cost equivalents without API keys. The open-source tool revealed 6.5M tokens ($4,924 at API pricing) over 35 days in one user's case.
Semble: Code Search for AI Agents Using 98% Fewer Tokens Than grep+read
Semble is an open-source code search library for AI agents that combines static Model2Vec embeddings with BM25, running entirely on CPU. It indexes a repo in ~250ms and answers queries in ~1.5ms, achieving 0.854 NDCG@10 — 99% of a 137M-parameter transformer's quality — while using 98% fewer tokens than grep+read.